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Invia la tua candidatura per i programmi di accelerazione e/o pre-accelerazione.
Le candidature sono aperte a chiunque (non è necessario essere uno studente o un ex studente di Bocconi) ovunque.
Termine: 8 gennaio 2025.
In an era where data accumulation accelerates yet actionable insights lag, Scavenger AI emerges as a pivotal tool for businesses seeking to refine decision-making processes through generative AI and data-driven solutions.
Scavenger AI was created by Felix Beissel and Maximilian Hahnenkamp. They witnessed firsthand how organizations, overwhelmed by data, often falter in extracting timely and pertinent insights necessary for strategic decisions. This realization spurred them to develop Scavenger AI, a platform designed to function as a comprehensive AI business consultant.
The service streamlines the transformation of raw data into strategic insights, allowing companies to pose essential business questions and receive detailed analyses rapidly. By automating data cleansing, applying tailored statistical models, and presenting findings in a user-friendly dashboard, Scavenger AI facilitates a more efficient allocation of resources and sharpens the focus on critical business drivers.
We had the opportunity to speak with Felix and Maximilian and asked them to share the story behind Scavenger, their future goals as founders, and the advice they would offer to current and aspiring entrepreneurs.
Watch the full interview here!
Both of us were working in big corporates and saw a big problem first hand:
Companies have tons of data and are creating more every day but are lacking the time and the resources to convert them into insights. Which for a decision-maker is obviously a big problem, if you have to make a decision but do not have the necessary insights into your data.
When we started conducting initial customer interviews, we quickly realized that no matter which industry or which company size, all of the people we interacted with shared this problem.
All decision-makers we talked to were telling us how important it is to incorporate data-driven decision-making inside a company but managers rarely open Python themselves to run algorithms on their data and detect relations inside them. Which leads to a situation where managers in big companies need to wait weeks for answers from their analytics departments or engage a consultancy and smaller firms may lack data-driven decision making at all.
We thought that with the current technology available we can solve problems like this in seconds without the need of wasting time and resources.
We try to be as close as possible to our customers to always iterate the product regarding their feedback.
At the moment we are at a stage where we are doing development partnerships with the corporates. We launched our MVP in November and are now developing it together with our partners into a full-fledged product.
This approach has helped us a lot in generating positive customer feedback as we could not be closer to the customers in product development.
We both met at Bocconi University, where we studied EMIT (Felix) and Management (Max) and we were both very happy about the vibrant environment that surrounds the university. When we saw the opening call from B4i it was a no-brainer for us to apply and we were extremely happy when we got accepted to be able to enter this context once more.
We can not stretch it enough about how much B4i helped us and we attribute a major share of our recent funding round to the great support from B4i. The whole team is incredibly helpful, knowledgeable and available 24/7, which helped us a lot, as this is exactly what you need at such an early stage.
We are basically using the new funding to expand our team and develop the technological infrastructure to meet current customer requirements and launch the software on the market.
We know that we are building a highly technical and complex solution, yet easy to use for customers. In order to achieve that we need the best talent out there that joins our already great team to make that happen.
Additionally we are in the lucky situation to have a lot of customer demand, which also was the initial reason for the funding round. In order to deal with the demand we need to increase our infrastructure and launch the product into the market, because we always say it would be a shame to leave those revenues behind.
Do’s
Execution goes over everything else at an early stage. We saw that it is important to always have your bigger goal and vision in mind but in the end you need to put a lot of emphasis on execution.
Talk to potential customers as early as possible. You do not need to have a product yet, to go out there and validate it to see if you are on the right track.
Get into the right environment and create a network. Especially in the beginning you need to be open to receive advice and need the people you can get the right advice from. There are always people that have experienced your journey and are smarter than you are - use their advice.
Don’ts
Do not hire too fast. In the beginning it is very tempting to hire the first person you come across as you want to be fast and get your project starting. This might cost you a few months and money that would have been better spent on a longer recruitment process.
Do not be too stuck with your idea but listen to the market feedback. The platform and features you are building might not be aligned with what your customers really want.
Do not take any investment offered just for the sake of money. In the beginning it is very tempting to overlook investment conditions and be blinded by the well-needed money. Luckily we had great advisors and turned down several offers, which would have been huge mistakes.